code: def get_features_from_fn(self, input_fn, predict=True):
      with tf.Graph().as_default() as g:
          result = self._call_input_fn(
              input_fn, tf.estimator.ModeKeys.PREDICT
          )
          features, initializer = parse_input_fn_result(result)
          if type(features) == tuple and predict:
              features = features[0]
          with tf.compat.v1.Session(
              config=self._session_config
          ) as sess:
              sess.run(initializer)
              output = []
              while True:
                  try:
                      output.append(sess.run(features))
                  except tf.errors.OutOfRangeError:
                      break
          return output, features
  
file_path: finetune/finetune/util/indico_estimator.py
imports: import numpy
  import tensorflow
label_desc: Use image node_id 2 for calling the IndicoEstimator obj's underlying member method code with example usage: obj.get_features_from_fn(input_fn, predict) and returns: output,  features